Pathways To Data
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Author | : Shane Safir |
Publisher | : Corwin |
Total Pages | : 281 |
Release | : 2021-02-12 |
Genre | : Education |
ISBN | : 1071812661 |
Radically reimagine our ways of being, learning, and doing Education can be transformed if we eradicate our fixation on big data like standardized test scores as the supreme measure of equity and learning. Instead of the focus being on "fixing" and "filling" academic gaps, we must envision and rebuild the system from the student up—with classrooms, schools and systems built around students’ brilliance, cultural wealth, and intellectual potential. Street data reminds us that what is measurable is not the same as what is valuable and that data can be humanizing, liberatory and healing. By breaking down street data fundamentals: what it is, how to gather it, and how it can complement other forms of data to guide a school or district’s equity journey, Safir and Dugan offer an actionable framework for school transformation. Written for educators and policymakers, this book · Offers fresh ideas and innovative tools to apply immediately · Provides an asset-based model to help educators look for what’s right in our students and communities instead of seeking what’s wrong · Explores a different application of data, from its capacity to help us diagnose root causes of inequity, to its potential to transform learning, and its power to reshape adult culture Now is the time to take an antiracist stance, interrogate our assumptions about knowledge, measurement, and what really matters when it comes to educating young people.
Author | : Nick Salafsky |
Publisher | : Island Press |
Total Pages | : 330 |
Release | : 2021-12-02 |
Genre | : Nature |
ISBN | : 1642831352 |
As environmental problems grow larger and more pressing, conservation work has increasingly emphasized broad approaches to combat global-scale crises of biodiversity loss, invasive species, and climate change. Pathways to Success is a modern guide to building large-scale transformative conservation programs capable of tackling the complex issues we now face. In this strikingly illustrated volume, coauthors Nick Salafsky and Richard Margoluis walk readers through fundamental concepts of effective program-level design, helping them to think strategically about project coordination, funding, and stakeholder input. Pathways to Success is the definitive guide for conservation program managers and funders who want to increase the effectiveness of their work combating climate change, species extinctions, and the many challenges we face to keep our planet livable.
Author | : Ulrika Jägare |
Publisher | : John Wiley & Sons |
Total Pages | : 423 |
Release | : 2019-06-12 |
Genre | : Computers |
ISBN | : 1119566274 |
All the answers to your data science questions Over half of all businesses are using data science to generate insights and value from big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability from scratch, starting with the “what” and the “why” of data science and covering what it takes to lead and nurture a top-notch team of data scientists. With this book, you’ll learn how to incorporate data science as a strategic function into any business, large or small. Find solutions to your real-life challenges as you uncover the stories and value hidden within data. Learn exactly what data science is and why it’s important Adopt a data-driven mindset as the foundation to success Understand the processes and common roadblocks behind data science Keep your data science program focused on generating business value Nurture a top-quality data science team In non-technical language, Data Science Strategy For Dummies outlines new perspectives and strategies to effectively lead analytics and data science functions to create real value.
Author | : Jerry W. Hedge |
Publisher | : |
Total Pages | : 373 |
Release | : 2020 |
Genre | : Business & Economics |
ISBN | : 0190907789 |
"Major changes have occurred in the workplace during the last several decades that have transformed the nature of work, and our preparation for work. In recent years, we have seen the globalization of thousands of companies and most industries, organizational downsizing and restructuring, greater use of information technology at work, changes in work contracts, and the growth of various alternative education and work strategies and schedules"--
Author | : Avrim Blum |
Publisher | : Cambridge University Press |
Total Pages | : 433 |
Release | : 2020-01-23 |
Genre | : Computers |
ISBN | : 1108617360 |
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Author | : Nenad Blau |
Publisher | : Springer |
Total Pages | : 880 |
Release | : 2014-07-08 |
Genre | : Medical |
ISBN | : 3642403379 |
This book, combining and updating two previous editions, is a unique source of information on the diagnosis, treatment, and follow-up of metabolic diseases. The clinical and laboratory data characteristic of rare metabolic conditions can be bewildering for both clinicians and laboratory personnel. Reference laboratory data are scattered, and clinical descriptions may be obscure. The Physician’s Guide documents the features of more than five hundred conditions, grouped according to type of disorder, organ system affected (e.g. liver, kidney, etc) or phenotype (e.g. neurological, hepatic, etc). Relevant clinical findings are provided and pathological values for diagnostic metabolites highlighted. Guidance on appropriate biochemical genetic testing is provided. Established experimental therapeutic protocols are described, with recommendations on follow-up and monitoring. The authors are acknowledged experts, and the book will be a valuable desk reference for all who deal with inherited metabolic diseases.
Author | : Hadley Wickham |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 521 |
Release | : 2016-12-12 |
Genre | : Computers |
ISBN | : 1491910364 |
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Author | : Amy L. Affelt |
Publisher | : Information Today |
Total Pages | : 0 |
Release | : 2015 |
Genre | : Big data |
ISBN | : 9781573875110 |
Amy Affelt, author of The Accidental Data Scientist, notes that "Librarians and information professionals have always worked with data in order to meet the information needs of their constituents, thus 'Big Data' is not a new concept for them." With The Accidental Data Scientist, Amy Affelt shows information professionals how to leverage their skills and training to master emerging tools, techniques, and vocabulary; create mission-critical Big Data research deliverables; and discover rewarding new career opportunities by embracing their inner Data Scientist.
Author | : Nicholas Weller |
Publisher | : Cambridge University Press |
Total Pages | : 173 |
Release | : 2014-07-03 |
Genre | : Political Science |
ISBN | : 1107041066 |
This book introduces 'pathway analysis', a method to combine large and small-N research techniques and to aid understanding of causal mechanisms.
Author | : National Academies of Sciences, Engineering, and Medicine |
Publisher | : National Academies Press |
Total Pages | : 139 |
Release | : 2018-11-11 |
Genre | : Education |
ISBN | : 0309475597 |
Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.